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dc.contributor.authorSankaranarayanan, Aswin C.
Xu, Lina
Studer, Christoph
Li, Yun
Kelly, Kevin F.
Baraniuk, Richard G.
dc.date.accessioned 2017-05-12T15:04:32Z
dc.date.available 2017-05-12T15:04:32Z
dc.date.issued 2015
dc.identifier.citation Sankaranarayanan, Aswin C., Xu, Lina, Studer, Christoph, et al.. "Video Compressive Sensing for Spatial Multiplexing Cameras Using Motion-Flow Models." SIAM Journal on Imaging Sciences, 8, no. 3 (2015) SIAM: 1489-1518. http://dx.doi.org/10.1137/140983124.
dc.identifier.urihttps://hdl.handle.net/1911/94225
dc.description.abstract Spatial multiplexing cameras (SMCs) acquire a (typically static) scene through a series of coded projections using a spatial light modulator (e.g., a digital micromirror device) and a few optical sensors. This approach finds use in imaging applications where full-frame sensors are either too expensive (e.g., for short-wave infrared wavelengths) or unavailable. Existing SMC systems reconstruct static scenes using techniques from compressive sensing (CS). For videos, however, existing acquisition and recovery methods deliver poor quality. In this paper, we propose the CS multiscale video (CS-MUVI) sensing and recovery framework for high-quality video acquisition and recovery using SMCs. Our framework features novel sensing matrices that enable the efficient computation of a low-resolution video preview, while enabling high-resolution video recovery using convex optimization. To further improve the quality of the reconstructed videos, we extract optical-flow estimates from the low-resolution previews and impose them as constraints in the recovery procedure. We demonstrate the efficacy of our CS-MUVI framework for a host of synthetic and real measured SMC video data, and we show that high-quality videos can be recovered at roughly $60\times$ compression.
dc.language.iso eng
dc.publisher SIAM
dc.rights Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
dc.title Video Compressive Sensing for Spatial Multiplexing Cameras Using Motion-Flow Models
dc.type Journal article
dc.citation.journalTitle SIAM Journal on Imaging Sciences
dc.subject.keywordvideo compressive sensing
optical flow
measurement matrix design
spatial multiplexing cameras
dc.citation.volumeNumber 8
dc.citation.issueNumber 3
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1137/140983124
dc.type.publication publisher version
dc.citation.firstpage 1489
dc.citation.lastpage 1518


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